Identifying wheat root traits and regulatory genes for nitrogen uptake efficiency

Wheat (Triticum spp.) is a particularly important crop for food security, providing 20% of worldwide calorie intake. Food production is not meeting the projected global demand of an increase of 2.4% p.a. Improvement of resource capture in wheat could help meet this demand. Nitrogen (N) is an essential macronutrient for plant growth and development; however, nitrogen use efficiency (NUE) for cereal production is only 33%. Domestication of modern varieties of wheat may have lost potentially beneficial agronomic traits, particularly in the root system. Optimisation of root system architecture could profoundly improve nitrogen uptake efficiency (NUpE) and in turn increase the yield potential of the crop. Using ancestral wheat germplasm and mapping populations, desirable traits may be identified and bred back into commercial wheat varieties to increase yield potential. Using a high-throughput hydroponic root phenotyping system, N-dependent root traits have been identified in wheat mapping populations. Using transcriptomic analyses, the gene expression profile of a candidate N-dependent root QTL has been identified. Using a new root phenotyping system, X-ray micro-computed tomography (μCT), a three-dimensional representation of wheat roots can now be imaged in soil. A selection of the same mapping lines have been used for 3D μCT analysis based on field NUpE parameters to identify promising root traits in both seedlings and mature plants

(p,q)-form Kaehler Electromagnetism

We present a gauge invariant generalization of Maxwell's equations and p-form electromagnetism to Kaehler spacetimes.Comment: 5 pages, LaTe

Allometry of sodium requirements and mineral lick use among herbivorous mammals

Sodium (Na) plays a critical role in the functioning of terrestrial ecosystems. In Na-poor regions, plant consumers may experience Na deficiency and adapt by seeking supplementary Na resources. This can markedly impact animal behavior, space-use, and co-existence, with concomitant impacts on ecosystems. Many studies have noted that Na-seeking behaviors, such as soil consumption from mineral licks, are predominately observed for larger-bodied herbivores. However, the mechanisms that drive interspecific variation in Na deficiency and mineral lick use remain poorly understood. Here, we examine whether allometric scaling of Na requirements can explain variation in mineral lick use by herbivorous and omnivorous mammals. We 1) collated data from published literature to derive an allometric scaling of Na requirements in mammals, 2) compared predicted Na requirements to estimated Na intake of mammal communities in three globally distant sites: the Peruvian Amazon, Kalahari Desert, and Malaysian Borneo and 3) examined the relationship between predicted Na deficiency and mineral lick use utilizing camera-trap and mammal abundance data at each site. We found that minimum daily Na maintenance requirements in mammals scaled allometrically at a higher factor (BM0.91 (CI: 0.80–1.0)) than that of food and water Na intake (BM0.71–0.79), indicating that larger species may be more susceptible to Na limitation. This aligned with a positive association between mineral lick use and body mass (BM), as well as Na deficiency, by species at all sites, and increased artificial salt and mineral lick consumption by larger-bodied mammals in the Kalahari. Our results suggest that larger herbivores may be more sensitive to anthropogenic impacts to Na availability, which may alter their functional roles in ecosystems, particularly in Na-poor regions. Further research is needed to explore the consequences of changing Na availability on animals and ecosystems, as well as advance our understanding of Na physiology in mammals

Thirty years after Marr’s vision: levels of analysis in cognitive science

Thirty years after the publication of Marr’s seminal book Vision (Marr, 1982) the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has (either implicitly or explicitly) been downplayed or eliminated both by reductionist neuroscience approaches (from below) that seek to account for behaviour from the implementation level and by Bayesian approaches (from above) that seek to account for behaviour in purely computational-level terms

Feedback training induces a bias for detecting happiness or fear in facial expressions that generalises to a novel task

AbstractMany psychological disorders are characterised by insensitivities or biases in the processing of subtle facial expressions of emotion. Training using expression morph sequences which vary the intensity of expressions may be able to address such deficits. In the current study participants were shown expressions from either happy or fearful intensity morph sequences, and trained to detect the target emotion (e.g., happy in the happy sequence) as being present in low intensity expressions. Training transfer was tested using a six alternative forced choice emotion labelling task with varying intensity expressions, which participants completed before and after training. Training increased false alarms for the target emotion in the transfer task. Hit rate for the target emotion did not increase once adjustment was made for the increase in false alarms. This suggests that training causes a bias for detecting the target emotion which generalises outside of the training task. However it does not increase accuracy for detecting the target emotion. The results are discussed in terms of the training’s utility in addressing different types of emotion processing deficits in psychological disorders

Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks

© 1992-2012 IEEE. We address the complex problem of reliably segmenting root structure from soil in X-ray Computed Tomography (CT) images. We utilise a deep learning approach, and propose a state-of-the-art multi-resolution architecture based on encoder-decoders. While previous work in encoder-decoders implies the use of multiple resolutions simply by downsampling and upsampling images, we make this process explicit, with branches of the network tasked separately with obtaining local high-resolution segmentation, and wider low-resolution contextual information. The complete network is a memory efficient implementation that is still able to resolve small root detail in large volumetric images. We compare against a number of different encoder-decoder based architectures from the literature, as well as a popular existing image analysis tool designed for root CT segmentation. We show qualitatively and quantitatively that a multi-resolution approach offers substantial accuracy improvements over a both a small receptive field size in a deep network, or a larger receptive field in a shallower network. We then further improve performance using an incremental learning approach, in which failures in the original network are used to generate harder negative training examples. Our proposed method requires no user interaction, is fully automatic, and identifies large and fine root material throughout the whole volume

Approximate solutions of the determinantal assignment problem and distance problems

The paper introduces the formulation of an exact algebrogeometric problem, the study of the Determinantal Assignment Problem (DAP) in the set up of design, where approximate solutions of the algebraic problem are sought. Integral part of the solution of the Approximate DAP is the computation of distance of a multivector from the Grassmann variety of a projective space. We examine the special case of the calculation of the minimum distance of a multivector in ∧2(ℝ5) from the Grassmann variety G 2(ℝ5). This problem is closely related to the problem of decomposing the multivector and finding its best decomposable approximation. We establish the existence of the best decomposition in a closed form and link the problem of distance to the decomposition of multivectors. The uniqueness of this decomposition is then examined and several new alternative decompositions are presented that solve our minimization problem based on the structure of the problem